### Most Recent Posts

**Vitruvion: A Generative Model of Parametric CAD Sketches** - 25 September 2021

## 2020

### September 2020

**Using 3D Printing to Develop Rapid-Response PPE Manufacturing** - 28 September 2020

**Video: Introduction to Convex Optimization** - 27 September 2020

**Video: Basics of Optimization** - 20 September 2020

**Video: Information Theory Basics** - 13 September 2020

**Video: The Gaussian Distribution** - 6 September 2020

### August 2020

**Video: Useful Inequalities and Limit Theorems** - 30 August 2020

**Video: Dependence and Independence** - 23 August 2020

**Video: Basics of Joint Probability** - 16 August 2020

**Video: Some Useful Probability Distributions** - 9 August 2020

**Video: Probability Density and Mass Functions** - 2 August 2020

### July 2020

**Video: Probability Spaces and Random Variables** - 26 July 2020

**Video: Why is Probability Important to Machine Learning?** - 19 July 2020

**Video: Why is the Gradient the Direction of Steepest Ascent** - 12 July 2020

**Video: Derivative as the Best Affine Approximation** - 5 July 2020

### June 2020

**Video: Partial Derivatives** - 28 June 2020

**Video: Basics of Differentiation** - 21 June 2020

**The ELBO without Jensen, Kullback, or Leibler** - 17 June 2020

**Starting a YouTube Channel** - 14 June 2020

## 2019

### December 2019

**Discrete Object Generation with Reversible Inductive Construction** - 2 December 2019

### July 2019

**Lab Progress: Laser Cutter** - 12 July 2019

### June 2019

**Efficient Optimization of Loops and Limits with Randomized Telescoping Sums** - 14 June 2019

### May 2019

**Lab Progress: 3D Printer Enclosures** - 1 May 2019

### March 2019

**Lab Complete: Assembling Tormach** - 1 March 2019

## 2018

### December 2018

**A Bayesian Nonparametric View on Count-Min Sketch** - 1 December 2018

### August 2018

**New Lab: Demolition** - 24 August 2018

### July 2018

**Moved to Princeton!** - 1 July 2018

## 2014

### September 2014

**Which research results will generalize?** - 2 September 2014

## 2013

### August 2013

**Prior knowledge and overfitting** - 26 August 2013

**ICML Highlight: Fast Dropout Training** - 1 August 2013

### June 2013

**Testing MCMC code, part 2: integration tests** - 10 June 2013

**Compressing genomes** - 5 June 2013

### May 2013

**Testing MCMC code, part 1: unit tests** - 20 May 2013

**The Central Limit Theorem** - 14 May 2013

**JIT compilation in MATLAB** - 13 May 2013

### April 2013

**Introspection in AI** - 29 April 2013

**Machine Learning Glossary** - 22 April 2013

**Optimal Spatial Prediction with Kriging** - 21 April 2013

**Fisher information** - 8 April 2013

**The Gumbel-Max Trick for Discrete Distributions** - 6 April 2013

### March 2013

**Pseudo-marginal MCMC** - 31 March 2013

**Chernoff's bound** - 25 March 2013

**Upcoming Conferences** - 24 March 2013

**Variational Inference (part 1)** - 22 March 2013

**Geometric means of distributions** - 18 March 2013

**Learning Theory: What Next?** - 15 March 2013

**Stochastic memoization in Haskell** - 14 March 2013

**Data compression and unsupervised learning, Part 2** - 12 March 2013

**An Auxiliary Variable Trick for MCMC** - 11 March 2013

**The Correct Birth/Death Jacobian for Mixture Models** - 8 March 2013

**A Geometric Intuition for Markov's Inequality** - 7 March 2013

**The Alias Method: Efficient Sampling with Many Discrete Outcomes** - 3 March 2013

### February 2013

**What is representation learning?** - 25 February 2013

**High-Dimensional Probability Estimation with Deep Density Models** - 22 February 2013

**Data compression and unsupervised learning** - 21 February 2013

**A Parallel Gamma Sampling Implementation** - 21 February 2013

**Exponential Families and Maximum Entropy** - 18 February 2013

**Learning Theory: Purely Theoretical?** - 15 February 2013

**The Fundamental Matrix of a Finite Markov Chain** - 15 February 2013

**Disconnectivity graphs** - 14 February 2013

**Correlation and Mutual Information** - 13 February 2013

**Getting above the fray with lifted inference** - 8 February 2013

**Variograms, Covariance functions and Stationarity** - 7 February 2013

**What the hell is representation? *** - 6 February 2013

**Predictive learning vs. representation learning** - 4 February 2013

### January 2013

**What is the Computational Capacity of the Brain?** - 30 January 2013

**Is AI scary?** - 30 January 2013

**Dealing with Reliability when Crowdsourcing** - 29 January 2013

**The Natural Gradient** - 25 January 2013

**Complexity of Inference in Bayesian Networks** - 24 January 2013

**It Depends on the Model** - 24 January 2013

**Markov chain centenary** - 23 January 2013

**Aversion of Inversion** - 22 January 2013

**Introductory post, and the invariance problem** - 21 January 2013

**DPMs and Consistency** - 17 January 2013

**Unbiased estimators of partition functions are basically lower bounds** - 14 January 2013

**Priors for Functional and Effective Connectivity** - 11 January 2013

**Computing Log-Sum-Exp** - 9 January 2013

**A Continuous Approach to Discrete MCMC** - 7 January 2013

**Bayesian nonparametrics in the real world** - 4 January 2013

**Asymptotic Equipartition of Markov Chains** - 3 January 2013

**Hashing, streaming and sketching** - 2 January 2013

**On representation and sparsity** - 1 January 2013

## 2012

### December 2012

**Nonparanormal Activity** - 27 December 2012

**Discriminative (supervised) Learning** - 26 December 2012

**Method of moments** - 25 December 2012

**Should neurons be interpretable?** - 24 December 2012

**Turning Theory into Algorithms** - 21 December 2012

**The "Computation" in Computational Neuroscience** - 20 December 2012

**The Poisson Estimator** - 19 December 2012

**Learning Image Features from Video** - 18 December 2012

**Healthy Competition?** - 17 December 2012

**New Blog** - 16 December 2012